The Role
Analyze large-scale audience, client, and vendor datasets to assess data quality, matching accuracy, connectivity, and coverage. Use SQL, Python or R, statistical analysis, exploratory analysis, and validation methods to identify anomalies, false positives, false negatives, and improvement opportunities. Create benchmarking and regression datasets, validate audience outputs, report insights, and collaborate with Product, Engineering, and Data Science teams to improve audience data products.
Summary Generated by Built In
Job Role: Data Analyst – Audience Analytics
Location: Hyderabad, India
Experience: 4+ Years
About AnblicksAnblicks is a Great Place to Work® Certified™ Data and AI company helping enterprises unlock the power of data through modern data platforms, cloud technologies, and advanced analytics. We partner with leading technology providers to deliver scalable, data-driven solutions that enable intelligent enterprises.
Role OverviewWe are looking for a skilled Data Analyst – Audience Analytics with strong expertise in SQL, Python, data quality, and statistical analysis to support the validation, measurement, and optimization of audience data products.
In this role, you will analyze large-scale client and vendor datasets, validate audience outputs and data connectivity, investigate matching inaccuracies, and identify opportunities to improve audience quality and coverage. You will collaborate with Product, Engineering, and Data Science teams to evaluate product performance, develop benchmarking datasets, and deliver actionable insights that support continuous product improvement.
The ideal candidate has strong analytical and problem-solving skills, exceptional attention to detail, and an interest in audience analytics, identity resolution, and data-driven marketing technology.
Key Responsibilities- Audience Data Analysis: Analyze audience files, internal crosswalks, and client/vendor datasets to identify fragmented connections, anomalous records, and incorrect person or household associations.
- Data Quality & Match Assessment: Investigate and quantify false positives, false negatives, and other data matching quality indicators.
- Validation & Testing: Validate audience outputs, matching behavior, and data connectivity across real-world business scenarios and use cases.
- SQL & Python Analytics: Use SQL and Python or R to query, process, profile, and analyze large and complex datasets.
- Benchmarking & Test Data: Create, maintain, and enhance datasets for testing, validation, benchmarking, and regression analysis.
- Exploratory Data Analysis: Perform detailed and ad hoc analyses to uncover patterns, anomalies, trends, and opportunities for improving audience data quality.
- Audience Optimization: Partner with Product and Engineering teams to improve matching accuracy, audience connectivity, data coverage, and overall product performance.
- Statistical Analysis: Apply appropriate analytical methods and quality metrics to evaluate audience matching effectiveness and data reliability.
- Reporting & Insights: Prepare reports and document findings, recommendations, quality trends, and performance insights for technical and business stakeholders.
- Cross-Functional Collaboration: Support the Lead Data Scientist and collaborate with Product, Engineering, and Data Science teams on validation, testing, and research initiatives.
- Continuous Improvement: Contribute to testing backlogs, validation workflows, quality monitoring, and measurement processes to improve audience product adoption and reliability.
- Bachelor's degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, or a related field.
- 4+ years of experience in data analytics, data quality, data validation, or a related analytical role.
- Strong proficiency in SQL, including complex queries, joins, aggregations, data profiling, and analysis of large datasets.
- Hands-on experience with Python or R for data analysis, data manipulation, and statistical evaluation.
- Strong understanding of data quality assessment, validation methodologies, and exploratory data analysis.
- Experience identifying anomalies, duplicates, inconsistencies, and patterns across complex datasets.
- Knowledge of statistical analysis and data-driven problem-solving techniques.
- Strong analytical thinking, attention to detail, and the ability to translate findings into actionable recommendations.
- Excellent communication skills and the ability to collaborate with cross-functional technical and business teams.
- Experience in audience analytics, audience generation, identity resolution, entity matching, or customer identity data.
- Familiarity with audience data products, data crosswalks, identity mapping, and person-level or household-level data relationships.
- Experience working with large-scale, data-intensive platforms and complex client/vendor datasets.
- Understanding of match-quality measurement, including false-positive and false-negative analysis.
- Experience creating benchmarking datasets, test scenarios, and regression testing workflows.
- Exposure to Customer Data Platforms (CDPs), MarTech, AdTech, audience intelligence, or digital marketing ecosystems.
- Familiarity with cloud-based data platforms such as Snowflake, Databricks, or equivalent technologies.
- You enjoy investigating complex datasets and identifying meaningful patterns and data quality issues.
- You can use SQL, Python, and statistical techniques to validate data and measure product effectiveness.
- You have a structured approach to problem-solving and can convert analytical findings into measurable improvements.
- You work effectively with cross-functional teams to enhance data accuracy, connectivity, and product performance.
Skills Required
- Bachelor's degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, or a related field.
- 4+ years of experience in data analytics, data quality, data validation, or a related analytical role.
- Strong proficiency in SQL, including complex queries, joins, aggregations, data profiling, and large-dataset analysis.
- Hands-on experience with Python or R for data analysis, data manipulation, and statistical evaluation.
- Strong understanding of data quality assessment, validation methodologies, and exploratory data analysis.
- Experience identifying anomalies, duplicates, inconsistencies, and patterns across complex datasets.
- Knowledge of statistical analysis and data-driven problem-solving techniques.
- Strong analytical thinking, attention to detail, and ability to translate findings into actionable recommendations.
- Excellent communication skills and ability to collaborate with cross-functional technical and business teams.
- Experience in audience analytics, audience generation, identity resolution, entity matching, or customer identity data.
- Familiarity with audience data products, data crosswalks, identity mapping, and person-level or household-level data relationships.
- Experience working with large-scale, data-intensive platforms and complex client/vendor datasets.
- Understanding of match-quality measurement, including false-positive and false-negative analysis.
- Experience creating benchmarking datasets, test scenarios, and regression testing workflows.
- Exposure to Customer Data Platforms, MarTech, AdTech, audience intelligence, or digital marketing ecosystems.
- Familiarity with cloud-based data platforms such as Snowflake, Databricks, or equivalent technologies.
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
